A Latent-Feature Plackett-Luce Model for Dyad Ranking Completion
نویسنده
چکیده
Dyad ranking is a specific type of preference learning problem, namely the problem of learning a model that is capable of ranking a set of feature vector pairs, called dyads. In this paper a situation is considered where feature vectors consists of identifiers only. A new method based on learning latent-features is introduced for this purpose. The method is evaluated on synthetic data and is applied on the problem of ranking from implicit feedback.
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